为智能体系统中的数字身份防护与克隆治理提供框架
DIRF: A Framework for Digital Identity Protection and Clone Governance in Agentic AI Systems
- 构建九个领域63项控制的统一安全框架
- 涵盖身份授权、溯源和收益分配等核心机制
- 适合平台方、法律机构与监管者参考使用
生成式人工智能的快速发展与广泛应用对个人身份完整性构成重大威胁，包括数字克隆、复杂伪造及身份数据的非法商业化。应对这些风险需建立强大的AI生成内容检测系统、强化法律框架与伦理规范。本文提出数字身份权利框架（DIRF），一个结构化的安全与治理模型，旨在保护行为、生物特征及人格化数字形象属性。该框架涵盖九个领域与63项控制措施，融合法律、技术和混合执行机制，保障数字身份的授权、可追溯性与收益分配。文中阐述其架构基础、执行策略与关键应用场景，旨在为平台建设者、法律实体与监管机构提供必要控制依据，以在智能驱动系统中落实身份权利。
原文摘要 · Abstract (English)
The rapid advancement and widespread adoption of generative artificial intelligence (AI) pose significant threats to the integrity of personal identity, including digital cloning, sophisticated impersonation, and the unauthorized monetization of identity-related data. Mitigating these risks necessitates the development of robust AI-generated content detection systems, enhanced legal frameworks, and ethical guidelines. This paper introduces the Digital Identity Rights Framework (DIRF), a structured security and governance model designed to protect behavioral, biometric, and personality-based digital likeness attributes to address this critical need. Structured across nine domains and 63 controls, DIRF integrates legal, technical, and hybrid enforcement mechanisms to secure digital identity consent, traceability, and monetization. We present the architectural foundations, enforcement strategies, and key use cases supporting the need for a unified framework. This work aims to inform platform builders, legal entities, and regulators about the essential controls needed to enforce identity rights in AI-driven systems.
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